Search results for: computer information systems

Authors: J. Szpor, K. Witczak, M. Storman, A. Orchel, D. Hodorowicz-Zaniewska, K. Okoń, A. Klimkowska

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Core needle biopsy (CNB) is well established as an important diagnostic tool in diagnosing breast cancer and it is now considered the initial method of choice for diagnosing breast disease. In comparison to fine needle aspiration (FNA), CNB provides more architectural information allowing for the evaluation of prognostic and predictive factors for breast cancer, including histological grade—one of three prognostic factors used to calculate the Nottingham Prognostic Index. Several studies have previously described the concordance rate between CNB and surgical excision specimen in determination of histological grade (HG). The concordance rate previously ascribed to overall grade varies widely across literature, ranging from 59-91%. The aim of this study is to see how the data looks like in material at authors’ institution and are the results as compared to those described in previous literature. The study population included 157 women with a breast tumor who underwent a core needle biopsy for breast carcinoma and a subsequent surgical excision of the tumor. Both materials were evaluated for the determination of histological grade (scale from 1 to 3). HG was assessed only in core needle biopsies containing at least 10 well preserved HPF with invasive tumor. The degree of concordance between CNB and surgical excision specimen for the determination of tumor grade was assessed by Cohen’s kappa coefficient. The level of agreement between core needle biopsy and surgical resection specimen for overall histologic grading was 73% (113 of 155 cases). CNB correctly predicted the grade of the surgical excision specimen in 21 cases for grade 1 tumors (Kappa coefficient κ = 0.525 95% CI (0.3634; 0.6818), 52 cases for grade 2 (Kappa coefficient κ = 0.5652 95% CI (0.458; 0.667) and 40 cases for stage 3 tumors (Kappa coefficient κ = 0.6154 95% CI (0.4862; 0.7309). The highest level of agreement was observed in grade 3 malignancies. In 9 of 42 (21%) discordant cases, the grade was higher in the CNB than in the surgical excision. This composed 6% of the overall discordance. These results correspond to the noted in the literature, showing that underestimation occurs more frequently than overestimation. This study shows that authors’ institution’s histologic grading of CNBs and surgical excisions shows a fairly good correlation and is consistent with findings in previous reports. Despite the inevitable limitations of CNB, CNB is an effective method for diagnosing breast cancer and managing treatment options. Assessment of tumour grade by CNB is useful for the planning of treatment, so in authors’ opinion it is worthy to implement it in daily practice.

Keywords: breast cancer, concordance, core needle biopsy, histological grade

Procedia PDF Downloads 214

Authors: Sami Houry

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Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

Procedia PDF Downloads 169

Authors: John Mark Payawal, Francis Aldrine Uy, John Paul Carreon

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This paper shows the application of Structural Health Monitoring, SHM into bridges. Bridges are structures built to provide passage over a physical obstruction such as rivers, chasms or roads. The Philippines has a total of 8,166 national bridges as published on the 2015 atlas of the Department of Public Works and Highways (DPWH) and only 2,924 or 35.81% of these bridges are in good condition. As a result, PHP 30.464 billion of the 2016 budget of DPWH is allocated on roads and/or bridges maintenance alone. Intensive spending is owed to the present practice of outdated manual inspection and assessment, and poor structural health monitoring of Philippine infrastructures. As the School of Civil, Environmental, & Geological Engineering of Mapua Institute of Technology (MIT) continuous its well driven passion in research based projects, a partnership with the Department of Science and Technology (DOST) and the DPWH launched the application of Structural Health Monitoring, (SHM) in Padre Jacinto Zamora Flyover. The flyover is located along Nagtahan Boulevard in Sta. Mesa, Manila that connects Brgy. 411 and Brgy. 635. It gives service to vehicles going from Lacson Avenue to Mabini Bridge passing over Legarda Flyover. The flyover is chosen among the many located bridges in Metro Manila as the focus of the pilot testing due to its site accessibility, and complete structural built plans and specifications necessary for SHM as provided by the Bureau of Design, BOD department of DPWH. This paper focuses on providing a method to calibrate theoretical readings from STAAD Vi8 Pro and sync the data to actual MEMS accelerometer readings. It is observed that while the design standards used in constructing the flyover was reflected on the model, actual readings of MEMS accelerometer display a large difference compared to the theoretical data ran and taken from STAAD Vi8 Pro. In achieving a true seismic response of the modeled bridge or hence syncing the theoretical data to the actual sensor reading also called as the independent variable of this paper, analysis using single degree of freedom (SDOF) of the flyover under free vibration without damping using STAAD Vi8 Pro is done. The earthquake excitation and bridge responses are subjected to earthquake ground motion in the form of ground acceleration or Peak Ground Acceleration, PGA. Translational acceleration load is used to simulate the ground motion of the time history analysis acceleration record in STAAD Vi8 Pro.

Keywords: accelerometer, analysis using single degree of freedom, micro electro mechanical system, peak ground acceleration, structural health monitoring

Procedia PDF Downloads 304

Authors: Abulbasit G. Abdulsayid, Zinab F. Abdulla, Asma A. Omer

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On the ground that the orifice plate is relatively inexpensive, requires very little maintenance and only calibrated during the occasion of plant turnaround, the orifice plate has turned to be in a real prevalent use in gas industry. Inaccuracy of measurement in the fiscal metering stations may highly be accounted to be the most vital factor for mischarges in the natural gas industry in Libya. A very trivial error in measurement can add up a fast escalating financial burden to the custodian transactions. The unaccounted gas quantity transferred annually via orifice plates in Libya, could be estimated in an extent of multi-million dollars. As the oil and gas wealth is the solely source of income to Libya, every effort is now being exerted to improve the accuracy of existing orifice metering facilities. Discharge coefficient has become pivotal in current researches undertaken in this regard. Hence, increasing the knowledge of the flow field in a typical orifice meter is indispensable. Recently and in a drastic pace, the CFD has become the most time and cost efficient versatile tool for in-depth analysis of fluid mechanics, heat and mass transfer of various industrial applications. Getting deeper into the physical phenomena lied beneath and predicting all relevant parameters and variables with high spatial and temporal resolution have been the greatest weighing pros counting for CFD. In this paper, flow phenomena for air passing through an orifice meter were numerically analyzed with CFD code based modeling, giving important information about the effect of orifice plate specifications on the discharge coefficient for three different tappings locations, i.e., flange tappings, D and D/2 tappings compared with vena contracta tappings. Discharge coefficients were paralleled with discharge coefficients estimated by ISO 5167. The influences of orifice plate bore thickness, orifice plate thickness, beveled angle, perpendicularity and buckling of the orifice plate, were all duly investigated. A case of an orifice meter whose pipe diameter of 2 in, beta ratio of 0.5 and Reynolds number of 91100, was taken as a model. The results highlighted that the discharge coefficients were highly responsive to the variation of plate specifications and under all cases, the discharge coefficients for D and D/2 tappings were very close to that of vena contracta tappings which were believed as an ideal arrangement. Also, in general sense, it was appreciated that the standard equation in ISO 5167, by which the discharge coefficient was calculated, cannot capture the variation of the plate specifications and thus further thorough considerations would be still needed.

Keywords: CFD, discharge coefficients, orifice meter, orifice plate specifications

Procedia PDF Downloads 107

Authors: Sylvie Sossou, Grégoire Gansou, Ildevert Egue

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Introduction: The mission of the family and the school is to educate and train citizens of the city. But the family’s values , parental roles, respect for life collapse in their traditional African form. Indeed laxity with regard to divorce, liberal ideas about child rearing influence the emotional life of the latter. Several causes may contribute to the decline in academic performance. In order to seek a psychological solution to the issue, a study was conducted in 6 schools at the 9th district in Cotonou, cosmopolitan city of Benin. Objective: To evaluate the impact of single parenthood on the psycho child development. Materials and Methods: Questionnaires and interviews were used to gather verbal information. The questionnaires were administered to parents and children (schoolchildren 4, 5 and six form) from 7 to 12 years in lone parenthood. The interview was done with teachers and school leaders. We identified 209 cases of children living with a "single-parent" and 68 single parents. Results: Of the 209 children surveyed the results showed that 116 children are cut relational triangle in early childhood (before 3 years). The psychological effects showed that the separation has caused sadness for 52 children, anger 22, shame 17, crying at 31 children, fear for 14, the silence at 58 children. In front of complete family’s children, these children experience feelings of aggression in 11.48%; sadness in 30.64%; 5.26% the shame, the 6.69% tears; jealousy in 2.39% and 2.87% of indifference. The option to get married in 44.15% of children is a challenge to want to give a happy childhood for their offspring; 22.01% feel rejected, there is uncertainty for 11.48% of cases and 25.36% didn’t give answer. 49, 76% of children want to see their family together; 7.65% are against to avoid disputes and in many cases to save the mother of the father's physical abuse. 27.75% of the ex-partners decline responsibility in the care of the child. Furthermore family difficulties affecting the intellectual capacities of children: 37.32% of children see school difficulties related to family problems despite all the pressure single-parent to see his child succeed. Single parenthood affects inter-family relations: pressure 33.97%; nervousness 24.88%; overprotection 29.18%; backbiting 11.96%, are the lives of these families. Conclusion: At the end of the investigation, results showed that there is a causal relationship between psychological disorders, academic difficulties of children and quality of parental relationships. Other cases may exist, but the lack of resources meant that we have only limited at 6 schools. Early psychological treatment for these children is needed.

Keywords: single-parent, psycho child, school, Cotonou

Procedia PDF Downloads 373

Authors: Sumit Kumar

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The present study aims to identify the factors responsible for the internal migration of students other than push & pull factors; associated with the source region and destination region, respectively, as classified in classical geography. But in this classification of factors responsible for the migration of students, an agency of individual and the family he/she belongs to, have not been recognized which has later become the centre of the argument for describing and analyzing migration in New Economic theory of migration and New Economics of labour migration respectively. In this backdrop, the present study aims to understand the agency of an individual and the family members regarding one’s migration for higher education. Therefore, this study draws upon New Economic theory of migration and New Economics of labour migration for identifying the agency of individual or family in the context of migration. Further, migration for higher education consists not only the decision to migrate but also where to migrate (location), which university, which college and which course to pursue, also. In order to understand the role of various individuals at various stage of student migration, present study seeks help from the social networking approach for migration which identifies the individuals who facilitate the process of migration by reducing negative externalities of migration through sharing information and various other sorts of help to the migrant. Furthermore, this study also aims to rank those individuals who have helped migrants at various stages of migration for higher education in taking a decision, along with the factors responsible for their migration on the basis of their perception. In order to fulfill the above mentioned objectives of this study, quantification of qualitative data (perception of respondents) has been done employing through frequency distribution analysis. Qualitative data has been collected at two levels but questionnaire survey was the tool for data collection at both the occasions. Twenty five students who have migrated to other state for the purpose of higher education have been approached for pre-questionnaire survey consisting open-ended questions while one hundred students belonging to the same clientele have been approached for questionnaire survey consisting close-ended questions. This study has identified social pressure, peer group pressure and parental pressure; variables not constituting push & pull factors, very important for students’ migration. They have been even assigned better ranked by the respondents than push factors. Further, self (migrant themselves) have been ranked followed by parents by the respondents when it comes to take various decisions attached with the process of migration. Therefore, it can be said without sounding cynical that there are other factors other than push & pull factors which do facilitate the process of migration for higher education not only at the level to migrate but also at other levels intrinsic to the process of migration for higher education.

Keywords: agency, migration for higher education, perception, push and pull factors

Procedia PDF Downloads 221

Authors: Jose Daniel Hoyos Giraldo, Jesus Hernan Jimenez Giraldo, Juan Pablo Alvarado Perilla

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Range and endurance are the main limitations of electric aircraft due to the nature of its source of power. The improvement of efficiency on this kind of systems is extremely meaningful to encourage the aircraft operation with less environmental impact. The propeller efficiency highly affects the overall efficiency of the propulsion system; hence its optimization can have an outstanding effect on the aircraft performance. An optimization method is applied to an aircraft propeller in order to maximize its range and endurance by estimating the best combination of geometrical parameters such as diameter and airfoil, chord and pitch distribution for a specific aircraft design at a certain cruise speed, then the rotational speed at which the propeller operates at minimum current consumption is estimated. The optimization is based on the Blade Element Momentum (BEM) method, additionally corrected to account for tip and hub losses, Mach number and rotational effects; furthermore an airfoil lift and drag coefficients approximation is implemented from Computational Fluid Dynamics (CFD) simulations supported by preliminary studies of grid independence and suitability of different turbulence models, to feed the BEM method, with the aim of achieve more reliable results. Additionally, Vortex Theory is employed to find the optimum pitch and chord distribution to achieve a minimum induced loss propeller design. Moreover, the optimization takes into account the well-known brushless motor model, thrust constraints for take-off runway limitations, maximum allowable propeller diameter due to aircraft height and maximum motor power. The BEM-CFD method is validated by comparing its predictions for a known APC propeller with both available experimental tests and APC reported performance curves which are based on Vortex Theory fed with the NASA Transonic Airfoil code, showing a adequate fitting with experimental data even more than reported APC data. Optimal propeller predictions are validated by wind tunnel tests, CFD propeller simulations and a study of how the propeller will perform if it replaces the one of on known aircraft. Some tendency charts relating a wide range of parameters such as diameter, voltage, pitch, rotational speed, current, propeller and electric efficiencies are obtained and discussed. The implementation of CFD tools shows an improvement in the accuracy of BEM predictions. Results also showed how a propeller has higher efficiency peaks when it operates at high rotational speed due to the higher Reynolds at which airfoils present lower drag. On the other hand, the behavior of the current consumption related to the propulsive efficiency shows counterintuitive results, the best range and endurance is not necessary achieved in an efficiency peak.

Keywords: BEM, blade design, CFD, electric aircraft, endurance, optimization, range

Procedia PDF Downloads 93

Authors: Leigh Ann Wilson, Melanie Borrego

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The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

Procedia PDF Downloads 266

Authors: Jialin Ma, Jia Meng

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Genomic features, the genome-based coordinates, are commonly used for the representation of biological features such as genes, RNA transcripts and transcription factor binding sites. For the analysis of RNA-related genomic features, such as RNA modification sites, a common task is to correlate these features with transcript components (5'UTR, CDS, 3'UTR) to explore their distribution characteristics in terms of transcriptomic coordinates, e.g., to examine whether a specific type of biological feature is enriched near transcription start sites. Existing approaches for performing these tasks involve the manipulation of a gene database, conversion from genome-based coordinate to transcript-based coordinate, and visualization methods that are capable of showing RNA transcript components and distribution of the features. These steps are complicated and time consuming, and this is especially true for researchers who are not familiar with relevant tools. To overcome this obstacle, we develop a dedicated web app TARF, which represents web toolkit for annotating RNA-related genomic features. TARF web tool intends to provide a web-based way to easily annotate and visualize RNA-related genomic features. Once a user has uploaded the features with BED format and specified a built-in transcript database or uploaded a customized gene database with GTF format, the tool could fulfill its three main functions. First, it adds annotation on gene and RNA transcript components. For every features provided by the user, the overlapping with RNA transcript components are identified, and the information is combined in one table which is available for copy and download. Summary statistics about ambiguous belongings are also carried out. Second, the tool provides a convenient visualization method of the features on single gene/transcript level. For the selected gene, the tool shows the features with gene model on genome-based view, and also maps the features to transcript-based coordinate and show the distribution against one single spliced RNA transcript. Third, a global transcriptomic view of the genomic features is generated utilizing the Guitar R/Bioconductor package. The distribution of features on RNA transcripts are normalized with respect to RNA transcript landmarks and the enrichment of the features on different RNA transcript components is demonstrated. We tested the newly developed TARF toolkit with 3 different types of genomics features related to chromatin H3K4me3, RNA N6-methyladenosine (m6A) and RNA 5-methylcytosine (m5C), which are obtained from ChIP-Seq, MeRIP-Seq and RNA BS-Seq data, respectively. TARF successfully revealed their respective distribution characteristics, i.e. H3K4me3, m6A and m5C are enriched near transcription starting sites, stop codons and 5’UTRs, respectively. Overall, TARF is a useful web toolkit for annotation and visualization of RNA-related genomic features, and should help simplify the analysis of various RNA-related genomic features, especially those related RNA modifications.

Keywords: RNA-related genomic features, annotation, visualization, web server

Procedia PDF Downloads 193

Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

Procedia PDF Downloads 120

Authors: Roberto Pili, Alessandro Romagnoli, Hartmut Spliethoff, Christoph Wieland

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Internal combustion engines (ICE) are today the most common energy system to drive vehicles and transportation systems. Numerous studies state that 50-60% of the fuel energy content is lost to the ambient as sensible heat. ORC offers a valuable alternative to recover such waste heat from ICE, leading to fuel energy savings and reduced emissions. In contrast, the additional weight of the ORC affects the net energy balance of the overall system and the ORC occupies additional volume that competes with vehicle transportation capacity. Consequently, a lower income from delivered freight or passenger tickets can be achieved. The economic feasibility of integrating an ORC into an ICE and the resulting economic impact of weight and volume have not been analyzed in open literature yet. This work intends to define such a benchmark for ORC applications in the transportation sector and investigates the current situation on the market. The applied methodology refers to the freight market, but it can be extended to passenger transportation as well. The economic parameter X is defined as the ratio between the variation of the freight revenues and the variation of fuel costs when an ORC is installed as a bottoming cycle for an ICE with respect to a reference case without ORC. A good economic situation is obtained when the reduction in fuel costs is higher than the reduction of revenues for the delivered freight, i.e. X<1. Through this constraint, a maximum allowable change of transport capacity for a given relative reduction in fuel consumption is determined. The specific fuel consumption is influenced by the ORC in two ways. Firstly because the transportable freight is reduced and secondly because the total weight of the vehicle is increased. Note, that the generated electricity of the ORC influences the size of the ICE and the fuel consumption as well. Taking the above dependencies into account, the limiting condition X = 1 results in a second order equation for the relative change in transported cargo. The described procedure is carried out for a typical city bus, a truck of 24-40 t of payload capacity, a middle-size freight train (1000 t), an inland water vessel (Va RoRo, 2500 t) and handysize-like vessel (25000 t). The maximum allowable mass and volume of the ORC are calculated in dependence of its efficiency in order to satisfy X < 1. Subsequently, these values are compared with weight and volume of commercial ORC products. For ships of any size, the situation appears already highly favorable. A different result is obtained for road and rail vehicles. For trains, the mass and the volume of common ORC products have to be reduced at least by 50%. For trucks and buses, the situation looks even worse. The findings of the present study show a theoretical and practical approach for the economic application of ORC in the transportation sector. In future works, the potential for volume and mass reduction of the ORC will be addressed, together with the integration of an economic assessment for the ORC.

Keywords: ORC, transportation, volume, weight

Procedia PDF Downloads 212

Authors: Abdulaziz Bashir Kutawa1, 2, *, Khairulmazmi Ahmad 1, 3, Mohd Zobir Hussein 4, Asgar Ali 5, * Mohd Aswad Abdul Wahab1, Amara Rafi3, Mahesh Tiran Gunasena1, 6, Muhammad Ziaur Rahman1, 7, Md Imam Hossain1, And Syazwan Afif Mohd Zobir1

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Various abiotic and biotic stresses have an impact on rice production all around the world. The most serious and prevalent disease in rice plants, known as rice blast, is one of the major obstacles to the production of rice. It is one of the diseases that has the greatest negative effects on rice farming globally, the disease is caused by a fungus called Magnaporthe grisae. Since nanoparticles were shown to have an inhibitory impact on certain types of fungus, nanotechnology is a novel notion to enhance agriculture by battling plant diseases. Utilizing nanocarrier systems enables the active chemicals to be absorbed, attached, and encapsulated to produce efficient nanodelivery formulations. The objectives of this research work were to determine the efficacy and mode of action of the nanofungicides (in-vitro) and in field conditions (in-vivo). Ionic gelation method was used in the development of the nanofungicides. Using the poisoned media method, the synthesized agronanofungicides' in-vitro antifungal activity was assessed against M. grisae. The potato dextrose agar (PDA) was amended in several concentrations; 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.15, 0.20, 0.25, 0.30, and 0.35 ppm for the nanofungicides. Medium with the only solvent served as a control. Every day, mycelial growth was measured, and PIRG (percentage inhibition of radial growth) was also computed. Every day, mycelial growth was measured, and PIRG (percentage inhibition of radial growth) was also computed. Based on the results of the zone of inhibition, the chitosan-hexaconazole agronanofungicide (2g/mL) was the most effective fungicide to inhibit the growth of the fungus with 100% inhibition at 0.2, 0.25, 0.30, and 0.35 ppm, respectively. Then followed by carbendazim analytical fungicide that inhibited the growth of the fungus (100%) at 5, 10, 25, 50, and 100 ppm, respectively. The least were found to be propiconazole and basamid fungicides with 100% inhibition only at 100 ppm. The scanning electron microscope (SEM), confocal laser scanning microscope (CLSM), and transmission electron microscope (TEM) were used to study the mechanisms of action of the M. grisae fungal cells. The results showed that both carbendazim, chitosan-hexaconazole, and HXE were found to be the most effective fungicides in disrupting the mycelia of the fungus, and internal structures of the fungal cells. The results of the field assessment showed that the CHDEN treatment (5g/L, double dosage) was found to be the most effective fungicide to reduce the intensity of the rice blast disease with DSI of 17.56%, lesion length (0.43 cm), DR of 82.44%, AUDPC of 260.54 Unit2, and PI of 65.33%, respectively. The least treatment was found to be chitosan-hexaconazole-dazomet (2.5g/L, MIC). The usage of CHDEN and CHEN nanofungicides will significantly assist in lessening the severity of rice blast in the fields, increasing output and profit for rice farmers.

Keywords: chitosan, hexaconazole, disease incidence, and magnaporthe grisae

Procedia PDF Downloads 50

Authors: Saem Lee, Thanh Nguyen, Hio-Jung Shin, Thomas Koellner

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Land-use management has an influence on the provision of ecosystem service in dynamic, agricultural landscapes. Agricultural land use is important for maintaining the productivity and sustainability of agricultural ecosystems. However, in Korea, intensive farming activities in this highland agricultural zone, the upper stream of Soyang has led to contaminated soil caused by over-use pesticides and fertilizers. This has led to decrease in water and soil quality, which has consequences for ecosystem services and human wellbeing. Conventional farming has still high percentage in this area and there is no special measure to prevent low water quality caused by farming activities. Therefore, the adoption of environmentally friendly farming has been considered one of the alternatives that lead to improved water quality and increase in biomass production. Concurrently, farm households with environmentally friendly farming have occupied still low rates. Therefore, our research involved a farm household survey spanning conventional farming, the farm in transition and organic farming in Soyang watershed. Another purpose of our research was to compare economic advantage of the farmers adopting environmentally friendly farming and non-adaptors and to investigate the different factors by logistic regression analysis with socio-economic and benefit-cost ratio variables. The results found that farmers with environmentally friendly farming tended to be younger than conventional farming and farmer in transition. They are similar in terms of gender which was predominately male. Farmers with environmentally friendly farming were more educated and had less farming experience than conventional farming and farmer in transition. Based on the benefit-cost analysis, total costs that farm in transition farmers spent for one year are about two times as much as the sum of costs in environmentally friendly farming. The benefit of organic farmers was assessed with 2,800 KRW per household per year. In logistic regression, the factors having statistical significance are subsidy and district, residence period and benefit-cost ratio. And district and residence period have the negative impact on the practice of environmentally friendly farming techniques. The results of our research make a valuable contribution to provide important information to describe Korean policy-making for agricultural and water management and to consider potential approaches to policy that would substantiate ways beneficial for sustainable resource management.

Keywords: organic farming, logistic regression, profitability, agricultural land-use

Procedia PDF Downloads 389

Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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Authors: Oskar Sekowski

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Current global warming causes changes in the traditional zones of viticulture worldwide. During 20th century, the average global air temperature increased by 0.89˚C. The models of climate change indicate that viticulture, currently concentrating in narrow geographic niches, may move towards the poles, to higher geographic latitudes. Global warming may cause changes in traditional viticulture regions. Therefore, there is a need to estimate the climatic conditions and climate change in areas that are not traditionally associated with viticulture, e.g., Poland. The primary objective of this paper is to prepare methodology to evaluate the climatic and meteorological potential for viticulture in Poland based on a case study. Moreover, the additional aim is to evaluate the climatic potential of a mesoregion where a university vineyard is located. The daily data of temperature, precipitation, insolation, and wind speed (1988-2018) from the meteorological station located in Łazy, southern Poland, was used to evaluate 15 climatological parameters and indices connected with viticulture. The next steps of the methodology are based on Geographic Information System methods. The topographical factors such as a slope gradient and slope exposure were created using Digital Elevation Models. The spatial distribution of climatological elements was interpolated by ordinary kriging. The values of each factor and indices were also ranked and classified. The viticultural potential was determined by integrating two suitability maps, i.e., the topographical and climatic ones, and by calculating the average for each pixel. Data analysis shows significant changes in heat accumulation indices that are driven by increases in maximum temperature, mostly increasing number of days with Tmax > 30˚C. The climatic conditions of this mesoregion are sufficient for vitis vinifera viticulture. The values of indicators and insolation are similar to those in the known wine regions located on similar geographical latitudes in Europe. The smallest threat to viticulture in study area is the occurrence of hail and the highest occurrence of frost in the winter. This research provides the basis for evaluating general suitability and climatologic potential for viticulture in Poland. To characterize the climatic potential for viticulture, it is necessary to assess the suitability of all climatological and topographical factors that can influence viticulture. The methodology used in this case study shows places where there is a possibility to create vineyards. It may also be helpful for wine-makers to select grape varieties.

Keywords: climatologic potential, climatic classification, Poland, viticulture

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Authors: J. Marie Hicks

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The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning.

Keywords: poetic inference, poetic word play, substitutional inference, word substitution

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Authors: Păcurar Diana Istina

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The indissoluble link between aesthetics and semiotics, the harmonization and semiotic understanding of the interactions between the viewer and the object being looked at, are the basis of the practical demonstration of the importance of aesthetic perception within the theater performance. The design of a theater performance includes several structures, some considered from the beginning, art forms (i.e., the text), others being represented by simple, common objects (e.g., scenographic elements), which, if reunited, can trigger a certain aesthetic perception. The audience is delivered, by the team involved in the performance, a series of auditory and visual signs with which they interact. It is necessary to explain some notions about the physiological support of the transformation of different types of stimuli at the level of the cerebral hemispheres. The cortex considered the superior integration center of extransecal and entanged stimuli, permanently processes the information received, but even if it is delivered at a constant rate, the generated response is individualized and is conditioned by a number of factors. Each changing situation represents a new opportunity for the viewer to cope with, developing feelings of different intensities that influence the generation of meanings and, therefore, the management of interactions. In this sense, aesthetic perception depends on the detection of the “correctness” of signs, the forms of which are associated with an aesthetic property. Fairness and aesthetic properties can have positive or negative values. Evaluating the emotions that generate judgment and implicitly aesthetic perception, whether we refer to visual emotions or auditory emotions, involves the integration of three areas of interest: Valence, arousal and context control. In this context, superior human cognitive processes, memory, interpretation, learning, attribution of meanings, etc., help trigger the mechanism of anticipation and, no less important, the identification of error. This ability to locate a short circuit produced in a series of successive events is fundamental in the process of forming an aesthetic perception. Our main purpose in this research is to investigate the possible conditions under which aesthetic perception and its minimum content are generated by all these structures and, in particular, by interactions with forms that are not commonly considered aesthetic forms. In order to demonstrate the quantitative and qualitative importance of the categories of signs used to construct a code for reading a certain message, but also to emphasize the importance of the order of using these indices, we have structured a mathematical analysis that has at its core the analysis of the percentage of signs used in a theater performance.

Keywords: semiology, aesthetics, theatre semiotics, theatre performance, structure, aesthetic perception

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Kamlesh Shashikant Dave

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The global financial crisis is rooted in the sub-prime crisis in U.S.A. During the boom years, mortgage brokers attracted by the big commission, encouraged buyers with poor credit to accept housing mortgages with little or no down payment and without credit check. A combination of low interest rates and large inflow of foreign funds during the booming years helped the banks to create easy credit conditions for many years. Banks lent money on the assumptions that housing price would continue to rise. Also the real estate bubble encouraged the demand for houses as financial assets .Banks and financial institutions later repackaged these debts with other high risk debts and sold them to worldwide investors creating financial instruments called collateral debt obligations (CDOs). With the rise in interest rate, mortgage payments rose and defaults among the subprime category of borrowers increased accordingly. Through the securitization of mortgage payments, a recession developed in the housing sector and consequently it was transmitted to the entire US economy and rest of the world. The financial credit crisis has moved the US and the global economy into recession. Indian economy has also affected by the spill over effects of the global financial crisis. Great saving habit among people, strong fundamentals, strong conservative and regulatory regime have saved Indian economy from going out of gear, though significant parts of the economy have slowed down. Industrial activity, particularly in the manufacturing and infrastructure sectors decelerated. The service sector too, slow in construction, transport, trade, communication, hotels and restaurants sub sectors. The financial crisis has some adverse impact on the IT sector. Exports had declined in absolute terms in October. Higher inputs costs and dampened demand have dented corporate margins while the uncertainty surrounding the crisis has affected business confidence. To summarize, reckless subprime lending, loose monetary policy of US, expansion of financial derivatives beyond acceptable norms and greed of Wall Street has led to this exceptional global financial and economic crisis. Thus, the global credit crisis of 2008 highlights the need to redesign both the global and domestic financial regulatory systems not only to properly address systematic risk but also to support its proper functioning (i.e financial stability).Such design requires: 1) Well managed financial institutions with effective corporate governance and risk management system 2) Disclosure requirements sufficient to support market discipline. 3)Proper mechanisms for resolving problem institution and 4) Mechanisms to protect financial services consumers in the event of financial institutions failure.

Keywords: FIIs, BSE, sensex, global impact

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Authors: Diego F. Carrillo-González, Milena Osorio, Natalia M. Cerro, Yasser Y. Lenis

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Introduction: mortality during the implantation and early embryonic development periods reach around 30% in different mammalian species. It has been described that progesterone (P4) and Arginine (Arg) play a beneficial role in establishing and maintaining early pregnancy in mammals. The combined effect between Arg and P4 on reproductive parameters in the rabbit species is not yet elucidated, to our best knowledge. Objective: to assess the effect of L-arginine and progesterone during the post-breeding period in female rabbits on the composition of the amniotic fluid, the placental structure, and the bone growth in their fetuses. Methods: crossbred female rabbits (n=16) were randomly distributed into four experimental groups (Ctrl, Arg, P4, and Arg+P4). In the control group, 0.9% saline solution was administered as a placebo, the Arg group was administered arginine (50 mg/kg BW) from day 4.5 to day 19 post-breeding, the P4 group was administered progesterone (Gestavec®, 1.5 mg/kg BW) from 24 hours to day 4 post-breeding and for the Arg+P4 group, an administration was performed under the same time and dose guidelines as the Arg and P4 treatments. Four females were sacrificed, and the amniotic fluid was collected and analyzed with rapid urine test strips, while the placenta and fetuses were processed in the laboratory to obtain histological plates. The percentage of deciduous, labyrinthine, and junctional zones was determined, and the length of the femur for each fetus was measured as an indicator of growth. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, A one-way analysis of variance (ANOVA) was performed, and a comparison of means was conducted by Tukey's test. Results: a higher density (p<0.05) was observed in the amniotic fluid for fetuses in the control group (1022±2.5g/mL) compared to the P4 (1015±5.3g/mL) and Arg+P4 (1016±4,9g/mL) groups. Additionally, the density of amniotic fluid in the Arg group (1021±2.5g/mL) was higher (p<0.05) than in the P4 group. The concentration of protein, glucose, and ascorbic acid had no statistical difference between treatments (p>0.05). The histological analysis of the uteroplacental regions, a statistical difference (p<0,05) in the proportion of deciduous zone was found between the P4 group (9.6±2.6%) when compared with the Ctrl (28.15±12.3%), and Arg+P4 (26.3±4.9) groups. In the analysis of the fetuses, the weight was higher for the Arg group (2.69±0.18), compared to the other groups (p<0.05), while a shorter length was observed (p<0.05) in the fetuses for the Arg+P4 group (25.97±1.17). However, no difference (p>0.05) was found when comparing the length of the developing femurs between the experimental groups. Conclusion: the combination of L-arginine and progesterone allows a reduction in the density of amniotic fluid, without affecting the protein, energy, and antioxidant components. However, the use of L-arginine stimulates weight gain in fetuses, without affecting size, which could be used to improve production parameters in rabbit production systems. In addition, the modification in the deciduous zone could show a placental adaptation based on the fetal growth process, however more specific studies on the placentation process are required.

Keywords: arginine, progesterone, rabbits, reproduction

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Authors: Mustafa M. Donma, Orkide Donma

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Anthropometric measurements are essential for obesity studies. Waist circumference (WC) is the most frequently used measure, and along with hip circumference (HC), it is used in most equations derived for the evaluation of obese individuals. Morbid obesity is the most severe clinical form of obesity, and such individuals may also exhibit some clinical findings leading to metabolic syndrome (MetS). Then, it becomes a requirement to discriminate morbid obese children with (MOMetS+) and without (MOMetS-) MetS. Almost all obesity indices can differentiate obese (OB) children from children with normal body mass index (N-BMI). However, not all of them are capable of making this distinction. A recently introduced anthropometric obesity index, waist circumference + hip circumference/2 ((WC+HC)/2), was confirmed to differ OB children from those with N-BMI, however it has not been tested whether it will find clinical usage for the differential diagnosis of MOMetS+ and MOMetS-. This study was designed to find out the availability of (WC+HC)/2 for the purpose and to compare the possible preponderance of it over some other anthropometric or fat-based obesity indices. Forty-five MOMetS+ and forty-five MOMetS- children were included in the study. Participants have submitted informed consent forms. The study protocol was approved by the Non-interventional Ethics Committee of Tekirdag Namik Kemal University. Anthropometric measurements were performed. Body mass index (BMI), waist-to-hip circumference (W/H), (WC+HC)/2, trunk-to-leg fat ratio (TLFR), trunk-to-appendicular fat ratio (TAFR), trunk fat+leg fat/2 ((trunk+leg fat)/2), diagnostic obesity notation model assessment index-2 (D2I) and fat mass index (FMI) were calculated for both groups. Study data was analyzed statistically, and 0.05 for p value was accepted as the statistical significance degree. Statistically higher BMI, WC, (WC+HC)/2, (trunk+leg fat)/2 values were found in MOMetS+ children than MOMetS- children. No statistically significant difference was detected for W/H, TLFR, TAFR, D2I, and FMI between two groups. The lack of difference between the groups in terms of FMI and D2I pointed out the fact that the recently developed fat-based index; (trunk+leg fat)/2 gives much more valuable information during the evaluation of MOMetS+ and MOMetS- children. Upon evaluation of the correlations, (WC+HC)/2 was strongly correlated with D2I and FMI in both MOMetS+ and MOMetS- groups. Neither D2I nor FMI was correlated with W/H. Strong correlations were calculated between (WC+HC)/2 and (trunk+leg fat)/2 in both MOMetS- (r=0.961; p<0.001) and MOMetS+ (r=0.936; p<0.001) groups. Partial correlations between (WC+HC)/2 and (trunk+leg fat)/2 after controlling the effect of basal metabolic rate were r=0.726; p<0.001 in MOMetS- group and r=0.932; p<0.001 in MOMetS+ group. The correlation in the latter group was higher than the first group. In conclusion, recently developed anthropometric obesity index (WC+HC)/2 and fat-based obesity index (trunk+leg fat)/2 were of preponderance over the previously introduced classical obesity indices such as W/H, D2I and FMI during the differential diagnosis of MOMetS+ and MOMetS- children.

Keywords: children, hip circumference, metabolic syndrome, morbid obesity, waist circumference

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Authors: C. Brecher, M. Fey, F. Du Bois-Reymond, S. Neus

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Additive manufacturing has emerged into a fast-growing section within the manufacturing technologies. Established machine tool manufacturers, such as DMG MORI, recently presented machine tools combining milling and laser welding. By this, machine tools can realize a higher degree of flexibility and a shorter production time. Still there are challenges that have to be accounted for in terms of maintaining the necessary machining accuracy - especially due to thermal effects arising through the use of high power laser processing units. To study the thermal behavior of laser-integrated machine tools, it is essential to analyze and simulate the thermal behavior of machine components, individual and assembled. This information will help to design a geometrically stable machine tool under the influence of high power laser processes. This paper presents an approach to decrease the loss of machining precision due to thermal impacts. Real effects of laser machining processes are considered and thus enable an optimized design of the machine tool, respective its components, in the early design phase. Core element of this approach is a matched FEM model considering all relevant variables arising, e.g. laser power, angle of laser beam, reflective coefficients and heat transfer coefficient. Hence, a systematic approach to obtain this matched FEM model is essential. Indicating the thermal behavior of structural components as well as predicting the laser beam path, to determine the relevant beam intensity on the structural components, there are the two constituent aspects of the method. To match the model both aspects of the method have to be combined and verified empirically. In this context, an essential machine component of a five axis machine tool, the turn-swivel table, serves as the demonstration object for the verification process. Therefore, a turn-swivel table test bench as well as an experimental set-up to measure the beam propagation were developed and are described in the paper. In addition to the empirical investigation, a simulative approach of the described types of experimental examination is presented. Concluding, it is shown that the method and a good understanding of the two core aspects, the thermo-elastic machine behavior and the laser beam path, as well as their combination helps designers to minimize the loss of precision in the early stages of the design phase.

Keywords: additive manufacturing, laser beam machining, machine tool, thermal effects

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Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: Yufeng Wu, Yifan Gu, Bin Li, Wei Wang

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Resource recycling process contains a subsystem with interactions of three dimensions including coupling allocation of primary and secondary resources, responsibility coordination of stakeholders in forward and reverse supply chains, and trans-boundary transfer of hidden resource and environmental responsibilities between regions. Overlap or lack of responsibilities is easy to appear at the intersection of the three management dimensions. It is urgent to make an overall design of the policy system for recycling resources. From theoretical perspective, this paper analyzes the unique external differences of resource and environment in various dimensions and explores the reason why the effects of trans-dimensional policies are strongly correlated. Taking the example of the copper resources contained in the waste electrical and electronic equipment, this paper constructs reduction effect accounting model of resources recycling and set four trans-dimensional policy scenarios including resources tax and environmental tax reform of the raw and secondary resources, application of extended producer responsibility system, promotion of clean development mechanism, and strict entry barriers of imported wastes. In these ways, the paper simulates the impact effect of resources recycling process on resource deduction and emission reduction of waste water and gas, and constructs trans-dimensional policy mix scenario through integrating dominant strategy. The results show that combined application of various dimensional policies can achieve incentive compatibility and the trans-dimensional policy mix scenario can reach a better effect. Compared with baseline scenario, this scenario will increase 91.06% copper resources reduction effect and improve emission reduction of waste water and gas by eight times from 2010 to 2030. This paper further analyzes the development orientation of policies in various dimension. In resource dimension, the combined application of compulsory, market and authentication methods should be promoted to improve the use ratio of secondary resources. In supply chain dimension, resource value, residual functional value and potential information value contained in waste products should be fully excavated to construct a circular business system. In regional dimension, it should give full play to the comparative advantages of manufacturing power to improve China’s voice in resource recycling in the world.

Keywords: resource recycling, trans-dimension, policy design, incentive compatibility, life cycle

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Authors: Selina Lin, Justin M Fan, Vincent Zhang, Cindy Chen, Daniel Lam, Jason Yan, Ning Zhang

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Depression is one of the most common mental disorders in the United States, and past studies have shown a concerning increase in the rates of depression in youth populations over time. Furthermore, depression is an especially important issue for Asian Americans because of the anti-Asian violence taking place during the COVID-19 pandemic. While Asian American adolescents are reluctant to seek help for mental health issues, past research has found a prevalence of depressive symptoms in them that have yet to be fully investigated. There have been studies conducted to understand and observe the impacts of multifarious factors influencing the mental well-being of Asian American adolescents; however, they have been generally limited to qualitative investigation, and very few have attempted to quantitatively evaluate the relationship between depression levels and a comprehensive list of factors for those levels at the same time. To better quantify these relationships, this project investigated the prevalence of depression in Asian American teenagers mainly from the Greater Philadelphia Region, aged 12 to 19, and, with an anonymous survey, asked participants 48 multiple-choice questions pertaining to demographic information, daily behaviors, school life, family life, depression levels (quantified by the PHQ-9 assessment), school and family support against depression. Each multiple-choice question was assigned as a factor and variable for statistical and dominance analysis to determine the most influential factors on depression levels of Asian American adolescents. The results were validated via Bootstrap analysis and t-tests. While certain influential factors identified in this survey are consistent with the literature, such as parent-child relationship and peer pressure, several dominant factors were relatively overlooked in the past. These factors include the parents’ relationship with each other, the satisfaction with body image, sex identity, support from the family and support from the school. More than 25% of participants desired more support from their families and schools in handling depression issues. This study implied that it is beneficial for Asian American parents and adolescents to take programs on parents’ relationships with each other, parent-child communication, mental health, and sexual identity. A culturally inclusive school environment and more accessible mental health services would be helpful for Asian American adolescents to combat depression. This survey-based study paved the way for further investigation of effective approaches for helping Asian American adolescents against depression.

Keywords: Asian American adolescents, depression, dominance analysis, t-test, bootstrap analysis

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Authors: Gabriel G. Gaft, Xayvinay Xiong, Amanda Sunday

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The emergent pandemic from COVID-19 virus has forced people to adjust to major changes. These changes include all elements of family and work life and required people to engage in novel behaviors. For many people, the social norms to which they have been accustomed no longer prevail. Not surprisingly, such enormous changes in daily life have been associated with greater problems in mental health; and research regarding ways in which mental health professionals can support people is more necessary than ever before. It is often useful to assess people’s reactions through surveys and utilize quantitative data to answer questions about coping strategies etc. It is also likely, however, that a host of individual factors are going to contribute to what might be considered 'good' or 'bad' coping mechanisms to a worldwide pandemic. To this end, qualitative studies—where the individual’s subjective experience is highlighted—are likely to provide more vital information for mental health professionals interested in supporting the particular person in front of them. This study reports on qualitative data, where X participants were asked questions about social distancing, coping strategies, and general attitudes towards social changes resulting from the COVID-19 pandemic. Informal interviews were conducted during the months of June-July 2020. Data were analyzed using Interpretative Phenomenological Analyses. Themes were identified first for each participant and then compared across different individual participants. Several findings emerged. First, all participants understood major health messages being imparted by governing bodies such as the CDC and WHO. The researchers feel this finding is important as it suggests health messages are at least being effectively communicated. Second, there was a clear trend for themes which highlighted the conflicting emotions participants felt about the changes they were expected to endure: positive and negative elements were identified, although a participant who had pre-existing conditions placed greater emphasis on the negative elements. One participant who was particularly interested in impression management also exclusively emphasized negative emotions. Third, participants who were able to reevaluate priorities—what Lazarus might call secondary appraisals—experienced social distancing as a positive rather than negative phenomenon. Finally, participants who were able to develop specific strategies—such as boundaries for work and self-care—reported themes of adjustment and contentment. Taken together, these findings suggest mental health practitioners can assist people to adjust more positively through specific techniques focusing on re-evaluation of life priorities and strategic coping skills.

Keywords: COVID-19, pandemic, phenomenology, virus

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Authors: J. A. N. Sandamali, R. P. Hewawasam, K. A. P. W. Jayatilaka, L. K. B. Mudduwa

Abstract:

Introduction: Doxorubicin is widely used in the treatment of solid organ tumors and hematological malignancies, but the dose-dependent cardiotoxicity due to free radical formation compromises its clinical utility. Therapeutic strategies which enhance cellular endogenous defense systems have been identified as promising approaches to combat oxidative stress-associated conditions. Cinnamomum zeylanicum (Ceylon cinnamon) has a number antioxidant compounds, which can effectively scavenge reactive oxygen including superoxide anions, hydroxyl radicals and as well as other free radicals. Therefore, the objective of the study was to elucidate the most effective dose of Cinnamomum bark extract which ameliorates doxorubicin-induced cardiotoxicity. Materials and methods: Wistar rats were divided into seven groups of 10 animals in each. Group 1: normal control (distilled water, orally, for 14 days, 10 mL/kg saline, ip, after 16 hours fast on the 11th day); Group 2: doxorubicin control (distilled water, orally, for 14 days, 18 mg/kg doxorubicin, ip, after 16 hour fast on the 11th day); Groups 3-7: five doses of freeze dried aqueous bark extracts (0.125, 0.25, 0.5, 1.0, 2.0g/kg, orally, daily for 14 days, 18 mg/kg doxorubicin, ip, after 16 hours fast on the 11th day). Animals were sacrificed on the 15th day and blood was collected for the estimation of cardiac troponin I (cTnI), AST and LDH concentrations and myocardial tissues were collected for histopathological assessment of myocardial damage and irreversible changes were graded by developing a score. Results: cTnI concentration of groups 1-7 were 0, 161.9, 128.6, 95.9, 38, 19.41 & 12.36 pg/mL showing significant differences (p<0.05) between group 2 and groups 4-7. In groups 1-7, serum AST concentration were 26.82, 68.1, 37.18, 36.23, 26.8, 26.62 & 22.43U/L and LDH concentrations were 1166.13, 2428.84, 1658.35, 1474.34, 1277.58, 1110.21 & 974.40U/L and a significant difference (p<0.05) was observed between group 2 and groups 3-7. The maximum score for myocardial necrosis was observed in group 2. Parallel to the increase of the dosage of plant extract, a gradual reduction of the score for myocardial necrosis was observed in groups 3-7. Reversible histological changes such as vacuolation, congestion were observed in group 2 and all plant treated groups. Haemorrhages, inflammatory cell infiltrations, and interstitial oedema were observed in group 2, but absent in groups treated with higher doses of the plant extract. Discussion & Conclusion: According to the in vitro antioxidant assays performed, Cinnamomum zeylanicum (Ceylon cinnamon) bark possesses high amounts of polyphenolic substances and high antioxidant activity. The present study showed that Cinnamomum zeylanicum extract at 2.0 g/kg possesses the most significant cardioprotective effect against doxorubicin-induced cardiotoxicity. It can be postulated that pretreatment with Cinnamomum bark extract may replenish the cardiomyocytes with antioxidants that are needed for the defense against oxidative stress induced by doxorubicin.

Keywords: cardioprotection, Cinnamomum zeylanicum, doxorubicin, free radicals

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Authors: Stefanie M. Vanneste, Stijn Goeminne

Abstract:

This paper studies the effect of political characteristics of 308 Flemish municipalities on their budget balance in the period 1995-2011. All local governments experience the same economic and financial setting, however some governments have high budget balances, while others have low budget balances. The aim of this paper is to explain the differences in municipal budget balances by a number of economic, socio-demographic and political variables. The economic and socio-demographic variables will be used as control variables, while the focus of this paper will be on the political variables. We test four hypotheses resulting from the literature, namely (i) the partisan hypothesis tests if left wing governments have lower budget balances, (ii) the fragmentation hypothesis stating that more fragmented governments have lower budget balances, (iii) the hypothesis regarding the power of the government, higher powered governments would resolve in higher budget balances, and (iv) the opportunistic budget cycle to test whether politicians manipulate the economic situation before elections in order to maximize their reelection possibilities and therefore have lower budget balances before elections. The contributions of our paper to the existing literature are multiple. First, we use the whole array of political variables and not just a selection of them. Second, we are dealing with a homogeneous database with the same budget and election rules, making it easier to focus on the political factors without having to control for the impact of differences in the political systems. Third, our research extends the existing literature on Flemish municipalities as this is the first dynamic research on local budget balances. We use a dynamic panel data model. Because of the two lagged dependent variables as explanatory variables, we employ the system GMM (Generalized Method of Moments) estimator. This is the best possible estimator as we are dealing with political panel data that is rather persistent. Our empirical results show that the effect of the ideological position and the power of the coalition are of less importance to explain the budget balance. The political fragmentation of the government on the other hand has a negative and significant effect on the budget balance. The more parties in a coalition the worse the budget balance is ceteris paribus. Our results also provide evidence of an opportunistic budget cycle, the budget balances are lower in pre-election years relative to the other years to try and increase the incumbents reelection possibilities. An additional finding is that the incremental effect of the budget balance is very important and should not be ignored like is being done in a lot of empirical research. The coefficients of the lagged dependent variables are always positive and very significant. This proves that the budget balance is subject to incrementalism. It is not possible to change the entire policy from one year to another so the actions taken in recent past years still have an impact on the current budget balance. Only a relatively small amount of research concerning the budget balance takes this considerable incremental effect into account. Our findings survive several robustness checks.

Keywords: budget balance, fragmentation, ideology, incrementalism, municipalities, opportunistic budget cycle, panel data, political characteristics, power, system GMM

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

Abstract:

As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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